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Articles

Big wind power: seven questions for turbulence research

References

  • AWEA. Basics of wind energy. https://www.awea.org/wind-101/basics-of-wind-energy. 2017.
  • Vermeer L, Sorensen J, Crespo A. Wind turbine wake aerodynamics. Prog Aerosp Sci. 2003;39:467–510.
  • Sørensen JN. Aerodynamic aspects of wind energy conversion. Annu Rev Fluid Mech. 2011;43:427–448.
  • Sanderse B, van der Pijl SP, Koren B. Review of computational fluid dynamics for wind turbine wake aerodynamics. Wind Energy. 2011;14:799–819.
  • Stevens RJ, Meneveau C. Flow structure and turbulence in wind farms. Annu Rev Fluid Mech. 2017;49:311–339.
  • Mehta D, Van Zuijlen AH, Koren B, et al. Large eddy simulation of wind farm aerodynamics: A review. J Wind Eng Ind Aerodyn. 2014;133:1–17.
  • Shakoor R, Hassan MY, Raheem A, et al. Wake effect modeling: A review of wind farm layout optimization using Jensens model. Renew Sustain Energy Rev. 2016;58:1048–1059.
  • Jensen NO. A note on wind generator interaction. Risø-M-2411, Risø National Laboratory, Roskilde; 1983.
  • Frandsen S. On the wind speed reduction in the center of large clusters of wind turbines. J Wind Eng Ind Aerodyn. 1992;39:251–265.
  • Newman B. The spacing of wind turbines in large arrays. J Energy Convers. 1977;16:169–171.
  • Lissaman P. Energy effectiveness of arbitrary arrays of wind turbines. AIAA Paper. 1979;79–0114:1–7.
  • Frandsen S, Barthelmie R, Pryor S, et al. Analytical modelling of wind speed deficit in large offshore wind farms. Wind Energy. 2006;9:39–53.
  • Stevens RJAM, Gayme DF, Meneveau C. Coupled wake boundary layer model of wind-farms. J Renew Sustain Energy. 2015;7(2):023115.
  • Stevens RJAM, Gayme DF, Meneveau C. Generalized coupled wake boundary layer model: applications and comparisons with field and LES data for two wind farms. Wind Energy. 2016;19(11):2023–2040.
  • Yeung P, Donzis D, Sreenivasan K. Dissipation, enstrophy and pressure statistics in turbulence simulations at high Reynolds numbers. J Fluid Mech. 2012;700:5–15.
  • Ishihara T, Gotoh T, Kaneda Y. Study of high-Reynolds number isotropic turbulence by direct numerical simulation. Ann Rev Fluid Mech. 2009;41:165–180.
  • Blevins RD. Applied fluid dynamics handbook. New York, Van Nostrand Reinhold Co., 1984. 568; p. 1984.
  • Peña A, Bechmann A, Conti D, et al. Shelter models and observations. DTU Wind Energy-E-Report-0092 (EN); 2015.
  • Katic I, Højstrup J, Jensen NO. A simple model for cluster efficiency. In: European wind energy association conference and exhibition; 1987. p. 407–410.
  • Troen I. A high resolution spectral model for flow in complex terrain. In: Ninth symposium on turbulence and diffusion, Roskilde; 1990. p. 417–420.
  • Mortensen NG, Landberg L, Rathmann O, et al. Wind atlas analysis and application program (wasp). In: Wind energy department: Scientific and technical progress 1999-2000. DTU; 2001. p. 1–30.
  • Larsen G, Madsen H, Thomsen K, et al. Wake meandering: a pragmatic approach. Wind Energy. 2008;11(4):377–395.
  • Madsen HA, Larsen GC, Larsen TJ, et al. Calibration and validation of the dynamic wake meandering model for implementation in an aeroelastic code. J Sol Energy Eng. 2010;132(4):041014.
  • Larsen TJ, Madsen HA, Larsen GC. Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm. Wind Energy. 2013;16(4):605–624.
  • Mann J. Wind field simulation. Probab Eng Mech. 1998;13(4):269–282.
  • Tennekes H, Lumley JL. A first course in turbulence. Cambridge, MA: MIT Press; 1972.
  • Shapiro CR, Gayme DF, Meneveau C. Modelling yawed wind turbine wakes: a lifting line approach. J Fluid Mech. 2018;841:R1.
  • Berkooz G, Holmes P, Lumley JL. The proper orthogonal decomposition in the analysis of turbulent flows. Annu Rev Fluid Mech. 1993;25(1):539–575.
  • VerHulst C, Meneveau C. Large eddy simulation study of the kinetic energy entrainment by energetic turbulent flow structures in large wind farms. Phys Fluids. 2014;26(2):025113.
  • Bastine D, Witha B, Wächter M, et al. POD analysis of a wind turbine wake in a turbulent atmospheric boundary layer. In: Journal of Physics: Conference Series; Vol. 524; IOP Publishing; 2014. p. 012153
  • Hamilton N, Tutkun M, Cal RB. Low-order representations of the canonical wind turbine array boundary layer via double proper orthogonal decomposition. Phys Fluids. 2016;28(2):025103.
  • Noack BR, Konstantin AN, Morzynskim N, et al. A hierarchy of low-dimensional models for the transient and post-transient cylinder wake. J Fluid Mech. 2003;497:335–363.
  • Bastine D, Vollmer L, Wächter M, et al. Stochastic wake modelling based on POD analysis. Energies. 2018;11(3):612.
  • Schmid PJ. Dynamic mode decomposition of numerical and experimental data. J Fluid Mech. 2010;656:5–28.
  • Iungo GV, Santoni-Ortiz C, Abkar M, et al. Data-driven reduced order model for prediction of wind turbine wakes. In: Journal of Physics: Conference Series; Vol. 625; IOP Publishing; 2015. p. 012009.
  • Debnath M, Santoni C, Leonardi S, et al. Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes. Phil Trans R Soc A. 2017;375(2091):20160108.
  • Annoni J, Gebraad PM, Scholbrock AK, et al. Analysis of axial-induction-based wind plant control using an engineering and a high-order wind plant model. Wind Energy. 2016;19(6):1135–1150.
  • Fleming PA, Ning A, Gebraad PM, et al. Wind plant system engineering through optimization of layout and yaw control. Wind Energy. 2016;19(2):329–344.
  • Shapiro CR, Bauweraerts P, Meyers J, et al. Model-based receding horizon control of wind farms for secondary frequency regulation. Wind Energy. 2017;20(7):1261–1275.
  • Shapiro CR, Meyers J, Meneveau C, et al. Dynamic wake modeling and state estimation for improved model-based receding horizon control of wind farms. In: American Control Conference (ACC); 2017. p. 709–716.
  • Calaf M, Meneveau C, Meyers J. Large eddy simulation study of fully developed wind-turbine array boundary layers. Phys Fluids. 2010;22:015110.
  • Meneveau C. The top-down model of wind farm boundary layers and its applications. J Turbulence. 2012;13:N7.
  • Allaerts D, Meyers J. Boundary-layer development and gravity waves in conventionally neutral wind farms. J Fluid Mech. 2017;814:95–130.
  • Meyers J, Meneveau C. Flow visualization using momentum and energy transport tubes and applications to turbulent flow in wind farms. J Fluid Mech. 2013;715:335–358.
  • Lebron J, Castillo L, Meneveau C. Experimental study of the kinetic energy budget in a wind turbine streamtube. J Turbulence. 2012;13:N43.
  • VerHulst C, Meneveau C. Altering kinetic energy entrainment in large eddy simulations of large wind farms using unconventional wind turbine actuator forcing. Energies. 2015;8(1):370–386.
  • Burton T, Sharpe D, Jenkins N. Wind energy handbook. Chichester (West Sussex): John Wiley and Sons, Ltd.; 2001.
  • Manwell JF, McGowan JG, Rogers AL. Wind energy explained: theory, design and application. Chichester (West Sussex): John Wiley and Sons; 2010.
  • Van Kuik GA. The Lanchester – Betz – Joukowsky limit. Wind Energy: Int J Prog Appl Wind Power Conversion Technol. 2007;10(3):289–291.
  • Denholm P, Hand M, Jackson M, et al. Land-use requirements of modern wind power plants in the United States. Golden, CO: National Renewable Energy Laboratory. 2009. p. 57
  • Luzzatto-Fegiz P, Caulfield CP. Entrainment model for fully-developed wind farms: Effects of atmospheric stability and an ideal limit for wind farm performance. Phys Rev Fluids. 2018;3(9):093802.
  • Juneja A, Lathrop D, Sreenivasan K, et al. Synthetic turbulence. Phys Rev E. 1994;49(6):5179.
  • Basu S, Foufoula-Georgiou E, Porté-Agel F. Synthetic turbulence, fractal interpolation, and large-eddy simulation. Phys Rev E. 2004;70(2):026310.
  • Wu X. Inflow turbulence generation methods. Annu Rev Fluid Mech. 2017;49:23–49.
  • Kleinhans D, Friedrich R, Schaffarczyk A, et al. Synthetic turbulence models for wind turbine applications. In: Progress in turbulence III. Springer; 2009. p. 111–114
  • Sahin AD, Sen Z. First-order Markov chain approach to wind speed modelling. J Wind Eng Ind Aerodyn. 2001;89(3–4):263–269.
  • Shamshad A, Bawadi M, Hussin WW, et al. First and second order Markov chain models for synthetic generation of wind speed time series. Energy. 2005;30(5):693–708.
  • Cleve J, Greiner M. Stochastic small-scale modelling of turbulent wind time series. In: Wind energy. Springer; 2007. p. 123–127.
  • Veers P. Three-dimensional wind simulation. Albuquerque, NM: Sandia National Labs; 1988.
  • Keck RE, Mikkelsen R, Troldborg N, et al. Synthetic atmospheric turbulence and wind shear in large eddy simulations of wind turbine wakes. Wind Energy. 2014;17(8):1247–1267.
  • Fung JCH, Hunt JC, Malik N, et al. Kinematic simulation of homogeneous turbulence by unsteady random fourier modes. J Fluid Mech. 1992;236:281–318.
  • Wilczek M, Stevens RJAM, Meneveau C. Spatio-temporal spectra in the logarithmic layer of wall turbulence: large-eddy simulations and simple models. J Fluid Mech. 2015;769:R1–R12.
  • Wilczek M, Stevens RJAM, Meneveau C. Height-dependence of spatio-temporal spectra of wall-bounded turbulence–les results and model predictions. J Turbulence. 2015;16(10):937–949.
  • Lukassen LJ, Stevens RJAM, Meneveau C, et al. Modeling space-time correlations of velocity fluctuations in wind farms. Wind Energy. 2018;21(7):474–487.
  • Mücke T, Kleinhans D, Peinke J. Atmospheric turbulence and its influence on the alternating loads on wind turbines. Wind Energy. 2011;14(2):301–316.
  • Hedevang E, Biss K, Cleve J, et al. Intermittent fingerprints in wind-turbine interactions. In: Progress in turbulence and wind energy IV. Springer; 2012. p. 243–246.
  • Wächter M, Heißelmann H, Hölling M, et al. The turbulent nature of the atmospheric boundary layer and its impact on the wind energy conversion process. J Turbulence. 2012;13:N26.
  • Milan P, Wächter M, Peinke J. Turbulent character of wind energy. Phys Rev Lett. 2013;110(13):138701.
  • Nielsen M, Larsen G, Hansen K. Simulation of inhomogeneous, non-stationary and non-Gaussian turbulent winds. In: Journal of Physics: Conference Series; Vol. 75; IOP Publishing; 2007. p. 012060.
  • Lind PG, Herráez I, Wächter M, et al. Fatigue load estimation through a simple stochastic model. Energies. 2014;7(12):8279–8293.
  • Raischel F, Scholz T, Lopes VV, et al. Uncovering wind turbine properties through two-dimensional stochastic modeling of wind dynamics. Phys Rev E. 2013;88(4):042146.
  • Berg J, Natarajan A, Mann J, et al. Gaussian vs non-Gaussian turbulence: impact on wind turbine loads. Wind Energy. 2016;19(11):1975–1989.
  • Rosales C, Meneveau C. A minimal multiscale Lagrangian map approach to synthesize non-Gaussian turbulent vector fields. Phys Fluids. 2006;18(7):075104.
  • Rosales C, Meneveau C. Anomalous scaling and intermittency in three-dimensional synthetic turbulence. Phys Rev E. 2008;78(1):016313.
  • Wu YT, Porté-Agel F. Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations. Boundary Layer Meteorol. 2011;138(3):345–366.
  • Stevens RJAM, Graham J, Meneveau C. A concurrent precursor inflow method for large eddy simulations and applications to finite length wind farms. Renew Energy. 2014;68:46–50.
  • Goit JP, Munters W, Meyers J. Optimal coordinated control of power extraction in LES of a wind farm with entrance effects. Energies. 2016;9(1):29.
  • Archer CL, Mirzaeisefat S, Lee S. Quantifying the sensitivity of wind farm performance to array layout options using large-eddy simulation. Geophys Res Lett. 2013;40(18):4963–4970.
  • Churchfield M, Lee S, Moriarty P. Overview of the simulator for wind farm application (SOWFA); 2012.
  • Sescu A, Meneveau C. Large-eddy simulation and single-column modeling of thermally stratified wind turbine arrays for fully developed, stationary atmospheric conditions. J Atmos Oceanic Technol. 2015;32(6):1144–1162.
  • Michalakes J, Dudhia J, Gill D, et al. The weather research and forecast model: software architecture and performance. In: Use of high performance computing in meteorology. World Scientific; 2005. p. 156–168
  • Munters W, Meneveau C, Meyers J. Turbulent inflow precursor method with time-varying direction for large-eddy simulations and applications to wind farms. Boundary Layer Meteorol. 2016;159(2):305–328.
  • Lundquist JK, Mirocha J, Kosovic B. Nesting large-eddy simulations within mesoscale simulations in WRF for wind energy applications. In: Proceedings of the Fifth International Symposium on Computational Wind Engineering, Chapel Hill, NC; May 2010. p. 23–27.
  • Talbot C, Bou-Zeid E, Smith J. Nested mesoscale large-eddy simulations with WRF: performance in real test cases. J Hydrometeorology. 2012;13(5):1421–1441.
  • Vanella M, Piomelli U, Balaras E. Effect of grid discontinuities on large-eddy simulation statistics and flow fields. J Turbulence. 2008;9:N32.
  • Ghate AS, Lele SK. Subfilter-scale enrichment of planetary boundary layer large eddy simulation using discrete Fourier–Gabor modes. J Fluid Mech. 2017;819:494–539.
  • Jimenez A, Crespo A, Migoya E, et al. Advances in large-eddy simulation of a wind turbine wake. J Phys Conf Ser. 2007;75:012041.
  • Lignarolo LE, Mehta D, Stevens RJAM. Validation of four LES and a vortex model against stereo-PIV measurements in the near wake of an actuator disc and a wind turbine. Renew Energy. 2016;94:510–523.
  • Sørensen JN, Shen WZ. Numerical modeling of wind turbine wakes. J Fluids Eng. 2002;124(2):393–399.
  • Martínez-Tossas LA, Churchfield MJ, Leonardi S. Large eddy simulations of the flow past wind turbines: actuator line and disk modeling. Wind Energy. 2015;18(6):1047–1060.
  • Martínez-Tossas LA, Churchfield MJ, Meneveau C. Optimal smoothing length scale for actuator line models of wind turbine blades based on Gaussian body force distribution. Wind Energy. 2017;20(6):1083–1096.
  • Keith D, DeCarolis J, Denkenberger D, et al. The influence of large-scale wind power on global climate. Proc Natl Acad Sci USA. 2004;101:16115.
  • Baidya-Roy S, Pacala SW, Walko RL. Can large scale wind farms affect local meteorology?. J Geophys Res. 2004;109:D19101.
  • Fiedler B, Bukovsky M. The effect of a giant wind farm on precipitation in a regional climate model. Environ Res Lett. 2011;6(4):045101.
  • Nygaard NG. Wakes in very large wind farms and the effect of neighbouring wind farms. In: Journal of Physics: Conference Series; Vol. 524; IOP Publishing; 2014. p. 012162.
  • Fitch AC, Olson JB, Lundquist JK. Local and mesoscale impacts of wind farms as parameterized in a mesoscale NWP model. Monthly Weather Rev. 2012;140(9):3017–3038.
  • Weidman P. Modified shape of the Eiffel Tower determined for an atmospheric boundary-layer wind profile. Phys Fluids. 2009;21(6):067102.

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